Comparer des méthodes

	Test de Goldfeld-Quandt pour l'hétéroscédasticité	Test de Breusch-Pagan pour l'hétéroscédasticité	Test de White pour l'hétéroscédasticité
Domaine	Économétrie	Économétrie	Économétrie
Famille	Hypothesis test	Regression model	Regression model
Année d'origine	1965	1979	1980
Auteur d'origine	Stephen Goldfeld & Richard Quandt	Trevor Breusch & Adrian Pagan	Halbert White
Type	F-ratio test for heteroskedasticity	Lagrange-multiplier test for heteroskedasticity	General test for heteroskedasticity
Source fondatrice	Goldfeld, S. M., & Quandt, R. E. (1965). Some tests for homoscedasticity. Journal of the American Statistical Association, 60(310), 539–547.	Breusch, T. S., & Pagan, A. R. (1979). A simple test for heteroscedasticity and random coefficient variation. Econometrica, 47(5), 1287–1294.	White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838.
Alias	GQ Test, Goldfeld-Quandt Heteroskedasticity Test, Split-Sample Variance Ratio Test, Goldfeld-Quandt Homojenlik Testi	BP test, Breusch-Pagan-Godfrey test, Lagrange multiplier test for heteroskedasticity, Breusch-Pagan değişen varyans testi	White's general heteroskedasticity test, White değişen varyans testi
Apparentées	3	3	3
Résumé	The Goldfeld-Quandt test, introduced by Stephen Goldfeld and Richard Quandt in 1965, is a classical diagnostic procedure for detecting heteroskedasticity in OLS regression. It operates by sorting observations according to a variable suspected of driving variance, omitting a central block, fitting separate regressions on the two tail sub-samples, and comparing their residual variances via an F-ratio. The test is particularly well-suited to situations where the error variance is believed to increase or decrease monotonically with an observed regressor.	The Breusch-Pagan test, introduced by Trevor Breusch and Adrian Pagan in 1979, is a Lagrange-multiplier test for heteroskedasticity — the condition where the variance of a regression's errors changes with the explanatory variables. It works by regressing the squared OLS residuals on candidate variables and checking whether they explain any of the residual variation, signalling that the constant-variance assumption is violated.	The White test, introduced by Halbert White in 1980, is a general test for heteroskedasticity that makes no assumption about its functional form. It regresses the squared OLS residuals on the regressors, their squares, and their cross-products, so it can detect heteroskedasticity related to any of these terms. The same 1980 paper introduced the heteroskedasticity-consistent ('White') standard errors that are the standard remedy when the test rejects.